Advertisement

Journal of Intelligent Manufacturing

, Volume 18, Issue 2, pp 223–232 | Cite as

Personnel scheduling in a complex logistic system: a railway application case

  • Arianna Alfieri
  • Leo Kroon
  • Steef van de Velde
Article

Abstract

In complex logistic systems, such as transportation systems, dealing with personnel scheduling is a non-trivial task. Duties have to be created and assigned to workers in a way to optimize a certain objective function. In this paper, in particular, we consider the case of scheduling train drivers on a railway subnetwork. Train driver scheduling involves the construction of feasible duties from a set of trips to be carried out by a number of train drivers. Each duty consists of a sequence of trips to be carried out by a single train driver on a single day. The duties should be such that: each trip is covered by at least one duty, each duty satisfies feasibility constraints, additional constraints involving the complete schedule are satisfied, one or several objectives are met. In this paper we focus on minimizing the number of duties and on maximizing the robustness of the obtained schedule for outside disruptions. We present an implicit column generation solution approach. We describe a heuristic procedure to find an initial feasible solution together with a heuristic branch-and-price algorithm based on a dynamic programming algorithm for the pricing-out of columns. We tested our approach on the timetable of the Intercity train series 500, 700, 1600 and 1700 of NS Reizigers, the largest Dutch operator of passengers trains.

Keywords

Personnel scheduling Logistic systems Branch-and-Price Set covering Railway application 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Balas E., Carrera M.C. (1990). A dynamic subgradient-based branch-and-bound procedure for set covering. Operations Research, 44: 25–42Google Scholar
  2. 2.
    Balas E., Ho A. (1980). Set covering algorithms using cutting planes, heuristics and subgradient optimization: A computational study. Mathematical Programming Study, 12: 37–60Google Scholar
  3. 3.
    Barnhart C., Johnson E.L., Nemhauser G.L., Savelsbergh M.W.P., Vance P.H. (1998). Branch–and–Price: Column generation for solving huge integer programs. Operations Research, 46: 316–329Google Scholar
  4. 4.
    Beasley J.E. (1990). A Lagrangian heuristic for set covering problems. Naval Research Logistics, 31:151–164CrossRefGoogle Scholar
  5. 5.
    Caprara, A., Fischetti, M., Guida, P. L., Toth, P., & Vigo, D. (1997). Solution of large scale railway crew planning problems: The Italian experience. Proceedings of the 7th International Workshop on Computer Aided Scheduling of Public Transport, MIT.Google Scholar
  6. 6.
    Caprara A., Fischetti M., Toth P., Vigo D., Guida P.L. (1997). Algorithms for railway crew management. Mathematical Programming, 79, 125–141Google Scholar
  7. 7.
    Caprara A., Fischetti M., Toth P. (1999). A heuristic method for the set covering problem. Operations Research, 47, 730–743Google Scholar
  8. 8.
    Desrosiers, J., Dumas, Y., Solomon, M. M., & Soumis, F. (1995). Time constrained routing and scheduling. In M.O. Ball et al. (Ed.), Handbooks in OR & MS (Vol. 8, pp. 35–139). Elsevier Science.Google Scholar
  9. 9.
    Fisher M.L., Kedia P. (1990). Optimal solutions for set covering/partitioning problems using dual heuristics. Management Science, 36, 674–688Google Scholar
  10. 10.
    Freling, R. (1997). Models and techniques for integrating vehicle and crew scheduling. Ph.D. Thesis, Erasmus University Rotterdam.Google Scholar
  11. 11.
    Hoffmann K.L., Padberg M.W. (1993). Solving airline crew scheduling problems by branch-and-cut. Management Science, 39, 657–682Google Scholar
  12. 12.
    Ryan D.M., Foster B.A. (1981) An integer programming approach to scheduling. In: Wren A. (eds). Computer scheduling of public transport urban passenger vehicle and crew scheduling. Amsterdam, North Holland, pp. 269-280Google Scholar
  13. 13.
    Savelsbergh M.W.P. (1997). A Branch-and-Price algorithm for the generalized assignment problem. Operations Research, 45, 831–841Google Scholar
  14. 14.
    Vance, P. H. (1993). Crew scheduling, cutting stock, and column generation: Solving huge integer programs. Ph.D. Thesis, Georgia Institute of Technology.Google Scholar
  15. 15.
    Vance, P. H., Atamturk, A., Barnhart, C., Gelman, E., Jonhson, E. L., Krishna, A., Mahidhara, D.,Nemhauser, G. L., & Rebello, R. (1997). A heuristic Branch-and-Price approach for the airline crew pairing problem. preprint.Google Scholar
  16. 16.
    Vance P.H., Barnhart C., Jonhson E.L., Nemhauser G.L. (1997). Airline crew Scheduling: a new formulation and decomposition algorithm. Operations Research, 45, 188–200CrossRefGoogle Scholar
  17. 17.
    Wedelin D. (1995). An algorithm for large scale 0-1 integer programming with application to airline crew scheduling. Annals of Operations Research, 57, 283–301CrossRefGoogle Scholar
  18. 18.
    Wren, A., & Fares Gualda, N.D. (1997). Integrated scheduling of buses and drivers. Proceedings of the 7th International Workshop on Computer Aided Scheduling of Public Transport, MIT.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Arianna Alfieri
    • 1
  • Leo Kroon
    • 2
  • Steef van de Velde
    • 2
  1. 1.Dipartimento dei Sistemi di Produzione ed Economia dell’AziendaPolitecnico di TorinoTorinoItaly
  2. 2.Rotterdam School of ManagementErasmus UniversityRotterdamThe Netherlands

Personalised recommendations